|
![]() |
|||
|
||||
OverviewFull Product DetailsAuthor: Umberto MichelucciPublisher: APress Imprint: APress Edition: 2nd ed. Weight: 0.773kg ISBN: 9781484280195ISBN 10: 1484280199 Pages: 380 Publication Date: 29 March 2022 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsChapter 1 : Optimization and Neural Networks.- Chapter 2: Hands-on with One Single Neuron.- Chapter 3: Feed Forward Neural Networks.-Chapter 4: Regularization.- Chapter 5: Advanced Optimizers.- Chapter 6: Hyperparameter Tuning.- Chapter 7: Convolutional Neural Networks.-Chapter 8: Brief Introduction to Recurrent Neural Networks.- Chapter 9: Autoencoders.- Chapter 10: Metric Analysis.- Chapter 11: General Adversarial Networks (GANs).- Appendix A: Introduction to Keras.- Appendix B: Customizing KerasReviewsAuthor InformationUmberto Michelucci is the founder and the chief AI scientist of TOELT – Advanced AI LAB LLC. He’s an expert in numerical simulation, statistics, data science, and machine learning. He has 15 years of practical experience in the fields of data warehouse, data science, and machine learning. His first book, Applied Deep Learning—A Case-Based Approach to Understanding Deep Neural Networks, was published in 2018. His second book, Convolutional and Recurrent Neural Networks Theory and Applications was published in 2019. He publishes his research regularly and gives lectures on machine learning and statistics at various universities. He holds a PhD in machine learning, and he is also a Google Developer Expert in Machine Learning based in Switzerland. Tab Content 6Author Website:Countries AvailableAll regions |